Empirical Analysis of the Driving Factors of China’s ‘Land Finance’ Mechanism Using Soft Budget Constraint Theory and the PLS-SEM Model

Abstract

“Land finance” refers to the key fiscal strategy in which local governments in China generate revenue through land grant premiums and land tax revenues. A burgeoning body of literature has focused on the driving factors of China’s land finance from different aspects including fiscal decentralization, revenue decentralization, competition among local governments, land marketization, infrastructure development, and economic development. However, little research has provided a comprehensive perspective integrating social, economic and institutional aspects to investigate the driving forces of these unique and profound issues in China. This study aims to investigate the driving factors and working mechanism of land finance. A theoretical and empirical model was proposed using soft budget constraint theory and least squares structural equation modeling (PLS-SEM). The panel data of 35 Chinese major cities were assessed between 2006 and 2015. The empirical results contend the following: (1) the land transfer and fiscal systems provide the key impetus for land financing because the land transfer system forms a stable modality, and the fiscal system is an important incentive for land financing; (2) the effects of the economic development and political system are insignificant; and (3) the political and land systems significantly influence economic development. Our contributions focus on two aspects. Firstly, a comprehensive framework of factors germane to land finance is constructed. Secondly, a new research methodology for land use study is proposed. To the best of our knowledge, the current study is the first to employ the PLS-SEM method to delineate and verify the influence paths between multiple driving factors and land finance in different cities. Hence, research reliability can be improved.

Sensory Attributes and Consumer Acceptability of 12 Microgreens Species

“…The PLS-SEM method is becoming an important multivariate technique for analyzing consumer preferences and buying behavior in both observational and experimental settings [36][37][38][39][40]. PLS-SEM firstly estimates the latent constructs' scores and then estimates path coefficient and correlation among the construct [41]. More specifically, the PLS-SEM can be used for modelling the relationships among both latent and single-item observed variables.…”

“…Finally, in the third stage, structural model parameters (so called path coefficients) were estimated using the ordinary least squares method. According to several authors, the PLS-SEM algorithm attains better statistical capability especially with small sample size and with data not normally distributed [41,45,46]. Once the measurement and structural models are specified, the composite reliability is used to evaluate the internal consistency of the construct measures.…”

Effects of Land Finance on Resource Misallocation in Chinese Cities during 2003–2017: A Dynamic Panel Econometric Analysis

“…Although this study for the first time analyzes the effects of land finance on resource allocation in China at national, regional, and urban tier levels, two limitations still deserve being paid attention, and they may become the possible research directions for further studies. First, due to the limitations of data availability, we adopt the shares of land leasing revenue to GDP to act as the proxy of land finance, while the impact of land finance from different uses (i.e., industrial, commercial, and housing) on resource misallocation may be not consistent, which should be explored in further studies [5]. Moreover, this study has analyzed the temporal dependence of resource misallocation by introducing the Dynamic Panel Econometric Model, while the spatial dependence of resource misallocation has not been fully analyzed; thus the Dynamic Spatial Econometric Model, which can make up for this research gap, may be adopted in further studies [27].…”

“…Since the reform and opening up in 1978, China's marketization has improved significantly, while there still exists the mechanism barrier of resource misallocation so far [1]. Due to the fiscal decentralization in 1994, there was sharp decline in local revenue, while the responsibilities of local expenditure basically remained unchanged, which led to the high fiscal pressure and local governments had to seek other revenue sources [2][3][4][5]. Since land leasing revenue does not belong to the budgetary revenues and should not be shared with the central government, it has become one of the most important solutions to promote urbanization, industrialization, and modernization in China [6,7].…”

China’s Provincial Eco-Efficiency and Its Driving Factors—Based on Network DEA and PLS-SEM Method

“…However, these five factors cannot be directly measured. The SEM model is a common method to solve this problem; that is, setting observation variables for latent variables that are difficult to be measured directly, and using the relationships between these observed variables that can be used for statistical analysis to study the relationships between latent variables [ 26 ]. The estimation of model parameters also needs to choose an appropriate method.…”